Towards lattice-based interactive pharmacophore exploration
Résumé
In medicinal chemistry, a pharmacophore denominates a spatial arrangement of chemical features shared by a group of molecules which is responsible for a favourable interaction with binding site of the studied target. We have recently designed a method that automatically computes pharmacophores from a large data set of molecules without any prior supervised selection of a small subset of molecules. The connections between the computed pharmacophores provide a hierarchical organization: the pharmacophore network. The latter is structured by pharmacophores’ size and contains a large number of them. The current work aims at developing a structure which a drug designer can use to support his analysis without having to repeatedly mine pharmacophores. For this purpose, we enhance the knowledge on the pharmacophore network organization by taking into account parent-children relations and/or grouping the pharmacophores into equivalence classes, i.e. sets of pharmacophores occurring in exactly the same molecules. Additionally, each pharmacophore is annotated with one or several quality measures (e.g. confidence or growth rate measurements), information that will be exploited later-on.
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Poster-SFCI-Lehembre.pdf (2.03 Mo)
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Lehembre_AbstractSFCI2021.pdf (61.15 Ko)
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| Origine | Fichiers produits par l'(les) auteur(s) |
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| Origine | Fichiers produits par l'(les) auteur(s) |
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